dc.contributor.author | Snášel, Václav | |
dc.contributor.author | Platoš, Jan | |
dc.contributor.author | Krömer, Pavel | |
dc.contributor.author | Abraham, Ajith | |
dc.contributor.author | Ouddane, Nabil | |
dc.contributor.author | Húsek, Dušan | |
dc.date.accessioned | 2011-01-07T08:19:13Z | |
dc.date.available | 2011-01-07T08:19:13Z | |
dc.date.issued | 2010 | |
dc.identifier.citation | Neural Network World. 2010, vol. 20, issue 5, p. 591-608. | en |
dc.identifier.issn | 1210-0552 | |
dc.identifier.uri | http://hdl.handle.net/10084/83522 | |
dc.description.abstract | Since their appearance in 1993, first approaching the Shannon limit, turbo codes have given a new direction in the channel encoding field, especially since they have been adopted for multiple norms of telecommunications such as deeper communication. A robust interleaver can significantly contribute to the overall performance a turbo code system. Search for a good interleaver is a complex combinatorial optimization problem. In this paper, we present genetic algorithms and differential evolution, two bio-inspired approaches that have proven the ability to solve non-trivial combinatorial optimization tasks, as promising optimization methods to find a well-performing interleaver for large frame sizes. | en |
dc.language.iso | en | en |
dc.publisher | Akademie věd České republiky, Ústav informatiky | en |
dc.publisher | České vysoké učení technické v Praze. Fakulta dopravní | |
dc.relation.ispartofseries | Neural Network World | en |
dc.title | Interleaver optimization using population based metaheuristics | en |
dc.type | article | en |
dc.identifier.location | Není ve fondu ÚK | en |
dc.identifier.wos | 000284915500002 | |